Neural network analysis of analog data, particularly vibration signals, has been used in the art to identify and diagnose problems with rotating machinery. As one example, in U.S. Pat. No. 5,361,628, Marko et al. disclose diagnostic testing and classification of automobile engines using a neural network, wherein subsampling and filtration are applied to a vibration signal band in order to avoid overloading the neural network.
In U.S Pat. No. 5,041,976, Marko et al. disclose a pattern recognition diagnostic system for electronic automotive control systems. System parameters passing between the controller and the engine, both measured and calculated, must be properly selected and formatted as multidimensional input vectors for a neural network, where each parameter value corresponds to one vector dimension. A back propagation neural network is trained by sampling several such multidimensional vectors as each engine diagnostic problem is manually induced. Back propagation is a synthesizing network primarily suited to receiving analog values on each input node and producing a numerical result on a single output node.
Other examples are described in U.S. Pat. No. 5,602,761, titled "Machine Performance Monitoring and Fault Classification Using an Exponentially Weighted Moving Average"; U.S. Pat. No. 5,566,092 titled "Machine Fault Diagnostics System and Method"; and U.S. Pat. No. 5,566,273 titled "Supervised Training of a Neural Network", all assigned to the assignee of the present invention.
When diagnosing a malfunction in a complex binary system, the number of possible malfunctions is typically very large because a failure may be indicated by as little as a single incorrect bit. For example, in a system stage of a complex manufacturing operation directed by an electrical logic controller, the cause of a malfunction may not be readily apparent, nor in some instances even the general location in the overall manufacturing operation where the malfunction took place. A stuck valve, unlatched safety gate, or faulty sensor may be diagnosed by electrical current or continuity testing, or by an incorrect bit value in the controller, if one knows where to look. When it becomes apparent that such an event has occurred, usually as a result of the production of incorrect product, an indication from conventional monitoring within the control system, or a complete breakdown in the manufacturing operation, the operation is interrupted and a highly skilled individual must be employed to identify what is wrong and determine how to fix it.
As the system complexity and the range of malfunction sources expand, typical approaches in trouble shooting are becoming less practical.